A new study published in the European Heart Journal showed that IL-Using electrocardiogram (ECG) data, a new artificial ...

One of the most promising aspects of AI in wildfire management is its capacity to detect complex, nonlinear relationships across massive, multidimensional datasets. Traditional fire prediction models ...

View software available in the Integrated Systems Biology and AI — Tailored Pharmacology and Precision Medicine Lab led by Hu ...

Work on deep residual learning is most-cited since 2000 and may become the top of the all-time list within five years, Nature analysis finds The most-cited scientific paper of the 21st century was ...

The increasing complexity of modern chemical engineering processes presents significant challenges for timely and accurate anomaly detection. Traditional ...

Press Release Helm.ai, a leading provider of advanced AI software for high-end ADAS, autonomous driving, and robotics automation, today introduced Helm.ai Driver, a real-time deep neural network (DNN) ...

This study addresses the growing demand for news text classification driven by the rapid expansion of internet information by proposing a classification algorithm based on a Bidirectional Gated ...

In diabetes care, AI has propelled the field forward through predictive modeling, decision support, and real-time glycemic ...

Penn Engineers have developed the first programmable chip that can train nonlinear neural networks using light—a breakthrough ...

Neural networks are one typical structure on which artificial intelligence can be based. The term neural describes their learning ability, which to some extent mimics the functioning of neurons in our ...

Intelligent nanophotonics, combining nanophotonics and machine learning, is transforming optical information processing. This ...